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spacex_dash_app.py
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spacex_dash_app.py
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# Assignment instructions https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_3/lab_theia_plotly_dash.md.html
# Steps to setup development environment
# pip3 install pandas dash
# wget "https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/datasets/spacex_launch_dash.csv"
# following code is a modified version of this skeleton which you can download with
# wget "https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/labs/module_3/spacex_dash_app.py"
# python3 spacex_dash_app.py
# Import required libraries
import pandas as pd
import dash
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output
import plotly.express as px
# Read the airline data into pandas dataframe
spacex_df = pd.read_csv("spacex_launch_dash.csv")
max_payload = spacex_df['Payload Mass (kg)'].max()
min_payload = spacex_df['Payload Mass (kg)'].min()
# Create a dash application
app = dash.Dash(__name__)
# Create an app layout
app.layout = html.Div(children=[html.H1('SpaceX Launch Records Dashboard',
style={'textAlign': 'center', 'color': '#503D36',
'font-size': 40}),
# TASK 1: Add a dropdown list to enable Launch Site selection
# The default select value is for ALL sites
# dcc.Dropdown(id='site-dropdown',...)
dcc.Dropdown(id='site-dropdown',
options=[
{'label': 'All Sites', 'value': 'ALL'},
{'label': 'CCAFS LC-40', 'value': 'CCAFS LC-40'},
{'label': 'VAFB SLC-4E', 'value': 'VAFB SLC-4E'},
{'label': 'KSC LC-39A', 'value': 'KSC LC-39A'},
{'label': 'CCAFS SLC-40', 'value': 'CCAFS SLC-40'}
],
value='ALL',
placeholder='Select a Launch Site here',
searchable=True
# style={'width':'80%','padding':'3px','font-size':'20px','text-align-last':'center'}
),
html.Br(),
# TASK 2: Add a pie chart to show the total successful launches count for all sites
# If a specific launch site was selected, show the Success vs. Failed counts for the site
html.Div(dcc.Graph(id='success-pie-chart')),
html.Br(),
html.P("Payload range (Kg):"),
# TASK 3: Add a slider to select payload range
# dcc.RangeSlider(id='payload-slider',...)
dcc.RangeSlider(id='payload-slider',
min=0,
max=10000,
step=1000,
value=[min_payload, max_payload]
),
# TASK 4: Add a scatter chart to show the correlation between payload and launch success
html.Div(dcc.Graph(id='success-payload-scatter-chart')),
])
# TASK 2:
# Add a callback function for `site-dropdown` as input, `success-pie-chart` as output
@app.callback(Output(component_id='success-pie-chart', component_property='figure'),
Input(component_id='site-dropdown', component_property='value'))
def get_pie_chart(entered_site):
filtered_df = spacex_df
if entered_site == 'ALL':
fig = px.pie(filtered_df, values='class',
names='Launch Site',
title='Success Count for all launch sites')
return fig
else:
# return the outcomes piechart for a selected site
filtered_df = spacex_df[spacex_df['Launch Site'] == entered_site]
filtered_df = filtered_df.groupby(['Launch Site', 'class']).size().reset_index(name='class count')
fig = px.pie(filtered_df, values='class count', names='class',
title=f"Total Success Launches for site {entered_site}")
return fig
# TASK 4:
# Add a callback function for `site-dropdown` and `payload-slider` as inputs, `success-payload-scatter-chart` as output
@app.callback(Output(component_id='success-payload-scatter-chart', component_property='figure'),
[Input(component_id='site-dropdown', component_property='value'),
Input(component_id='payload-slider', component_property='value')])
def scatter(entered_site, payload):
filtered_df = spacex_df[spacex_df['Payload Mass (kg)'].between(payload[0], payload[1])]
# thought reusing filtered_df may cause issues, but tried it out of curiosity and it seems to be working fine
if entered_site == 'ALL':
fig = px.scatter(filtered_df, x='Payload Mass (kg)', y='class', color='Booster Version Category',
title='Success count on Payload mass for all sites')
return fig
else:
fig = px.scatter(filtered_df[filtered_df['Launch Site'] == entered_site], x='Payload Mass (kg)', y='class',
color='Booster Version Category',
title=f"Success count on Payload mass for site {entered_site}")
return fig
# Run the app
if __name__ == '__main__':
app.run_server()